US5698089A - Sensor arrays for detecting analytes in fluids - Google Patents
Sensor arrays for detecting analytes in fluids Download PDFInfo
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- US5698089A US5698089A US08/689,227 US68922796A US5698089A US 5698089 A US5698089 A US 5698089A US 68922796 A US68922796 A US 68922796A US 5698089 A US5698089 A US 5698089A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N27/00—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means
- G01N27/02—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means by investigating impedance
- G01N27/04—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means by investigating impedance by investigating resistance
- G01N27/12—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means by investigating impedance by investigating resistance of a solid body in dependence upon absorption of a fluid; of a solid body in dependence upon reaction with a fluid, for detecting components in the fluid
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N27/00—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means
- G01N27/02—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means by investigating impedance
- G01N27/04—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means by investigating impedance by investigating resistance
- G01N27/12—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means by investigating impedance by investigating resistance of a solid body in dependence upon absorption of a fluid; of a solid body in dependence upon reaction with a fluid, for detecting components in the fluid
- G01N27/125—Composition of the body, e.g. the composition of its sensitive layer
- G01N27/126—Composition of the body, e.g. the composition of its sensitive layer comprising organic polymers
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
- G01N33/0004—Gaseous mixtures, e.g. polluted air
- G01N33/0009—General constructional details of gas analysers, e.g. portable test equipment
- G01N33/0027—General constructional details of gas analysers, e.g. portable test equipment concerning the detector
- G01N33/0031—General constructional details of gas analysers, e.g. portable test equipment concerning the detector comprising two or more sensors, e.g. a sensor array
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
- G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
- G01N33/483—Physical analysis of biological material
- G01N33/497—Physical analysis of biological material of gaseous biological material, e.g. breath
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y10—TECHNICAL SUBJECTS COVERED BY FORMER USPC
- Y10S—TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y10S435/00—Chemistry: molecular biology and microbiology
- Y10S435/817—Enzyme or microbe electrode
Definitions
- the field of the invention is electrical sensors for detecting analytes in fluids.
- the invention provides methods, apparatuses and expert systems for detecting analytes in fluids.
- the apparatuses include a chemical sensor comprising first and second conductive elements (e.g. electrical leads) electrically coupled to a chemically sensitive resistor which provides an electrical path between the conductive elements.
- the resistor comprises a plurality of alternating nonconductive regions (comprising a nonconductive organic polymer) and conductive regions (comprising a conductive material).
- the electrical path between the first and second conductive elements is transverse to (i.e. passes through) said plurality of alternating nonconductive and conductive regions.
- the resistor provides a difference in resistance between the conductive elements when contacted with a fluid comprising a chemical analyte at a first concentration, than when contacted with a fluid comprising the chemical analyte at a second different concentration.
- the electrical path through any given nonconductive region is typically on the order of 100 angstroms in length, providing a resistance of on the order of 100 m ⁇ across the region.
- Variability in chemical sensitivity from sensor to sensor is conveniently provided by qualitatively or quantitatively varying the composition of the conductive and/or nonconductive regions.
- the conductive material in each resistor is held constant (e.g. the same conductive material such as polypyrrole) while the nonconductive organic polymer varies between resistors (e.g. different plastics such as polystyrene).
- Arrays of such sensors are constructed with at least two sensors having different chemically sensitive resistors providing dissimilar differences in resistance.
- An electronic nose for detecting an analyte in a fluid may be constructed by using such arrays in conjunction with an electrical measuring device electrically connected to the conductive elements of each sensor.
- Such electronic noses may incorporate a variety of additional components including means for monitoring the temporal response of each sensor, assembling and analyzing sensor data to determine analyte identity, etc.
- FIGS. 1(A) and 1(A)-1 show an overview of sensor design; FIG. 1(B) shows an overview of sensor operation; FIG. 1(C) shows an overview of system operation.
- FIG. 2 Cyclic voltammogram of a poly(pyrrole)-coated platinum electrode.
- the electrolyte was 0.10M (C 4 H 9 ) 4 N! + ClO 4 ! - in acetonitrile, with a scan rate of 0.10 V s -1 .
- FIG. 3(A) shows the optical spectrum of a spin coated poly(pyrrole) film that had been washed with methanol to remove excess pyrrole and reduced phosphomolybdic acid.
- FIG. 3(B) shows the optical spectrum of a spin-coated poly(pyrrole) film on indium-tin-oxide after 10 potential cycles between +0.70 and -1.00 V vs. SCE in 0.10M (C 4 H 9 ) 4 N! + ClO 4 ! - in acetonitrile at a scan rate of 0.10 V -s -1 . The spectra were obtained in 0.10M KCl - H 2 O.
- FIGS. 4(A) and 4(A)-1 are a Schematic of a sensor array showing an enlargement of one of the modified ceramic capacitors used as sensing elements.
- the response patterns generated by the sensor array described in Table 3 are displayed for: FIG. 4(B) acetone; FIG. 4(C) benzene; and FIG. 4(D) ethanol.
- FIG. 5 Principle component analysis of autoscaled data from individual sensors containing different plasticizers.
- the numbers in the upper right hand corner of each square refer to the different sensor elements described in Table 3.
- FIGS. 6(A) & 6(B). Principle component analysis of data obtained from all sensors (Table 3). Conditions and symbols are identical to FIG. 5.
- FIG. 6A shows data represented in the first three principle components pc1, pc2 and pc3, while FIG. 6B shows the data when represented in pc1, pc2, and pc4.
- FIG. 6B shows the data when represented in pc1, pc2, and pc4.
- a higher degree of discrimination between some solvents could be obtained by considering the fourth principle component as illustrated by larger separations between chloroform, tetrahydrofuran, and isopropyl alcohol in FIG. 6B.
- FIG. 8 The resistance response of a poly(N-vinylpyrrolidone):carbon black (20 w/w % carbon black) sensor element to methanol, acetone, and benzene.
- Each trace is normalized by the resisance of the sensor element (approx. 125 ⁇ ) before each exposure.
- FIG. 9 First three principal components for the response of a carbon-black based sensor array with 10 element.
- the non-conductive components of the carbon-black composites used are listed in Table 3, and the resistors were 20 w/w % carbon black.
- the invention provides sensor arrays for detecting an analyte in a fluid for use in conjunction with an electrical measuring apparatus.
- These arrays comprise a plurality of compositionally different chemical sensors.
- Each sensor comprises at least first and second conductive leads electrically coupled to and separated by a chemically sensitive resistor.
- the leads may be any convenient conductive material, usually a metal, and may be interdigitized to maximize signal-to-noise strength.
- the resistor comprises a plurality of alternating nonconductive and conductive regions transverse to the electrical path between the conductive leads.
- the resistors are fabricated by blending a conductive material with a nonconductive organic polymer such that the electrically conductive path between the leads coupled to the resistor is interrupted by gaps of non-conductive organic polymer material.
- the matrix regions separating the particles provide the gaps.
- the nonconductive gaps range in path length from about 10 to 1,000 angstroms, usually on the order of 100 angstroms providing individual resistance of about 10 to 1,000 m ⁇ , usually on the order of 100 m ⁇ , across each gap.
- the path length and resistance of a given gap is not constant but rather is believed to change as the nonconductive organic polymer of the region absorbs, adsorbs or imbibes an analyte. Accordingly the dynamic aggregate resistance provided by these gaps in a given resistor is a function of analyte permeation of the nonconductive regions.
- the conductive material may also contribute to the dynamic aggregate resistance as a function of analyte permeation (e.g. when the conductive material is a conductive organic polymer such as polyprryole).
- conductive materials and nonconductive organic polymer materials can be used.
- Table 1 provides exemplary conductive materials for use in resistor fabrication; mixtures, such as of those listed, may also be used.
- Table 2 provides exemplary nonconductive organic polymer materials; blends and copolymers, such as of the polymers listed here, may also be used. Combinations, concentrations, blend stoichiometries, percolation thresholds, etc. are readily determined empirically by fabricating and screening prototype resistors (chemiresistors) as described below.
- the chemiresistors can be fabricated by many techniques such as, but not limited to, solution casting, suspension casting, and mechanical mixing.
- solution cast routes are advantageous because they provide homogeneous structures and ease of processing.
- resistor elements may be easily fabricated by spin, spray or dip coating. Since all elements of the resistor must be soluble, however, solution cast routes are somewhat limited in their applicability.
- Suspension casting still provides the possibility of spin, spray or dip coating but more heterogeneous structures than with solution casting are expected.
- mechanical mixing there are no solubility restrictions since it involves only the physical mixing of the resistor components, but device fabrication is more difficult since spin, spray and dip coating are no longer possible. A more detailed discussion of each of these follows.
- the chemiresistors can be fabricated by solution casting.
- the oxidation of pyrrole by phosphomolybdic acid presented herein represents such a system.
- the phosphomolybdic acid and pyrrole are dissolved in tetrahydrofuran (THF) and polymerization occurs upon solvent evaporation.
- THF tetrahydrofuran
- the choice of non-conductive polymers in this route is, of course, limited to those that are soluble in the reaction media.
- the doping procedure exposure to I 2 vapor, for instance
- the doping procedure can be performed on the blend to render the substituted poly(cyclooctatetraene) conductive.
- the choice of non-conductive polymers is limited to those that are soluble in the solvents that the undoped conducting polymer is soluble in and to those stable to the doping reaction.
- Certain conducting polymers can also be synthesized via a soluble precursor polymer. In these cases, blends between the precursor polymer and the non-conducting polymer can first be formed followed by chemical reaction to convert the precursor polymer into the desired conducting polymer. For instance poly(p-phenylene vinylene) can be synthesized through a soluble sulfonium precursor.
- Blends between this sulfonium precursor and the non-conductive polymer can be formed by solution casting. After which, the blend can be subjected to thermal treatment under vacuum to convert the sulfonium precursor to the desired poly(p-phenylene vinylene).
- suspension casting In suspension casting, one or more of the components of the resistor is suspended and the others dissolved in a common solvent. Suspension casting is a rather general technique applicable to a wide range of species, such as carbon blacks or colloidal metals, which can be suspended in solvents by vigorous mixing or sonication.
- the non-conductive polymer is dissolved in an appropriate solvent (such as THF, acetonitrile, water, etc.). Colloidal silver is then suspended in this solution and the resulting mixture is used to dip coat electrodes.
- an appropriate solvent such as THF, acetonitrile, water, etc.
- the individual elements can be optimized for a particular application by varying their chemical make up and morphologies.
- the chemical nature of the resistors determines to which analytes they will respond and their ability to distinguish different analytes.
- the relative ratio of conductive to insulating components determines the magnitude of the response since the resistance of the elements becomes more sensitive to sorbed molecules as the percolation threshold is approached.
- the film morphology is also important in determining response characteristics. For instance, thin films respond more quickly to analytes than do thick ones.
- sensors can be chosen that are appropriate for the analytes expected in a particular application, their concentrations, and the desired response times. Further optimization can then be performed in an iterative fashion as feedback on the performance of an array under particular conditions becomes available.
- the resistor may itself form a substrate for attaching the lead or the resistor.
- the structural rigidity of the resistors may be enhanced through a variety of techniques: chemical or radiation cross-linking of polymer components (dicumyl peroxide radical cross-linking, UV-radiation cross-linking of poly(olefins), sulfur cross-linking of rubbers, e-beam cross-linking of Nylon, etc.), the incorporation of polymers or other materials into the resistors to enhance physical properties (for instance, the incorporation of a high molecular weight, high transition metal (Tm) polymers), the incorporation of the resistor elements into supporting matrices such as clays or polymer networks (forming the resistor blends within poly-(methylmethacrylate) networks or within the lamellae of montmorillonite, for instance), etc.
- the resistor is deposited as a surface layer on a solid matrix which provides means for supporting the leads.
- the matrix is a chemically inert, non-
- Sensor arrays particularly well-suited to scaled up production are fabricated using integrated circuit (IC) design technologies.
- the chemiresistors can easily be integrated onto the front end of a simple amplifier interfaced to an A/D converter to efficiently feed the data stream directly into a neural network software or hardware analysis section.
- Micro-fabrication techniques can integrate the chemiresistors directly onto a micro-chip which contains the circuitry for analogue signal conditioning/processing and then data analysis. This provides for the production of millions of incrementally different sensor elements in a single manufacturing step using ink-jet technology. Controlled compositional gradients in the chemiresistor elements of a sensor array can be induced in a method analogous to how a color ink-jet printer deposits and mixes multiple colors.
- a sensor array of a million distinct elements only requires a 1 cm ⁇ 1 cm sized chip employing lithography at the 10 ⁇ m feature level, which is within the capacity of conventional commercial processing and deposition methods. This technology permits the production of sensitive, small-sized, stand-alone chemical sensors.
- Preferred sensor arrays have a predetermined inter-sensor variation in the structure or composition of the nonconductive organic polymer regions.
- the variation may be quantitative and/or qualitative.
- concentration of the nonconductive organic polymer in the blend can be varied across sensors.
- a variety of different organic polymers may be used in different sensors.
- An electronic nose for detecting an analyte in a fluid is fabricated by electrically coupling the sensor leads of an array of compositionally different sensors to an electrical measuring device.
- the device measures changes in resistivity at each sensor of the array, preferably simultaneously and preferably over time.
- the device includes signal processing means and is used in conjunction with a computer and data structure for comparing a given response profile, to a structure-response profile database for qualitative and quantitative analysis.
- a nose comprises at least ten, usually at least 100, and often at least 1000 different sensors though with mass deposition fabrication techniques described herein or otherwise known in the art, arrays of on the order of at least 10 6 sensors are readily produced.
- each resistor provides a first electrical resistance between its conductive leads when the resistor is contacted with a first fluid comprising a chemical analyte at a first concentration, and a second electrical resistance between its conductive leads when the resistor is contacted with a second fluid comprising the same chemical analyte at a second different concentration.
- the fluids may be liquid or gaseous in nature.
- the first and second fluids may reflect samples from two different environments, a change in the concentration of an analyte in a fluid sampled at two time points, a sample and a negative control, etc.
- the sensor array necessarily comprises sensors which respond differently to a change in an analyte concentration, i.e. the difference between the first and second electrical resistance of one sensor is different from the difference between the first second electrical resistance of another sensor.
- the temporal response of each sensor is recorded.
- the temporal response of each sensor may be normalized to a maximum percent increase and percent decrease in resistance which produces a response pattern associated with the exposure of the analyte.
- a structure-function database correlating analytes and response profiles is generated. Unknown analyte may then be characterized or identified using response pattern comparison and recognition algorithms.
- analyte detection systems comprising sensor arrays, an electrical measuring devise for detecting resistance across each chemiresistor, a computer, a data structure of sensor array response profiles, and a comparison algorithm are provided.
- the electrical measuring device is an integrated cicuit comprising neural network-based hardware and a digital-analog converter (DAC) multiplexed to each sensor, or a plurality of DACs, each connected to different sensor(s).
- DAC digital-analog converter
- analytes and fluids may be analyzed by the disclosed sensors, arrays and noses so long as the subject analyte is capable generating a differential response across a plurality of sensors of the array.
- Analyte applications include broad ranges of chemical classes such as organics such as alkanes, alkenes, alkynes, dienes, alicyclic hydrocarbons, arenes, alcohols, ethers, ketones, aldehydes, carbonyls, carbanions, polynuclear aromatics and derivatives of such organics, e.g. halide derivatives, etc., biomolecules such as sugars, isoprenes and isoprenoids, fatty acids and derivatives, etc.
- commercial applications of the sensors, arrays and noses include environmental toxicology and remediation, biomedicine, materials quality control, food and agricultural products monitoring, etc.
- the general method for using the disclosed sensors, arrays and electronic noses, for detecting the presence of an analyte in a fluid involves resistively sensing the presence of an analyte in a fluid with a chemical sensor comprising first and second conductive leads electrically coupled to and separated by a chemically sensitive resistor as described above by measuring a first resistance between the conductive leads when the resistor is contacted with a first fluid comprising an analyte at a first concentration and a second different resistance when the resistor is contacted with a second fluid comprising the analyte at a second different concentration.
- Poly(pyrrole) films used for conductivity, electrochemical, and optical measurements were prepared by injecting equal volumes of N 2 -purged solutions of pyrrole (1.50 mmoles in 4.0 ml dry tetrahydrofuran) and phosphomolybdic acid (0.75 mmoles in 4.0 ml tetrahydrofuran) into a N 2 -purged test tube. Once the two solutions were mixed, the yellow phosphomolybdic acid solution turned dark green, with no observable precipitation for several hours. This solution was used for film preparation within an hour of mixing.
- Plasticized poly(pyrrole) sensors were made by mixing two solutions, one of which contained 0.29 mmoles pyrrole in 5.0 ml tetrahydrofuran, with the other containing 0.25 mmoles phosphomolybdic acid and 30 mg of plasticizer in 5.0 ml of tetrahydrofuran. The mixture of these two solutions resulted in a w:w ratio of pyrrole to plasticizer of 2:3.
- An inexpensive, quick method for crating the chemiresistor array elements was accomplished by effecting a cross sectional cut through commercial 22 nF ceramic capacitors (Kemet Electronics Corporation).
- a data set obtained from a single exposure of the array to an odorant produced a set of descriptors (i.e. resistances), d i .
- the data obtained from multiple exposures thus produced a data matrix D where each row, designated by j, consisted of n descriptors describing a single member of the data set (i.e. a single exposure to an odor). Since the baseline resistance and the relative changes in resistance varied among sensor,s the data matrix was autoscaled before further processing (19). In this preprocessing technique, all the data associated with a single descriptor (i.e. a column in the data matrix) were centered around zero with unit standard deviation
- d i is the mean value for descriptor i and ⁇ i is the corresponding standard deviation.
- Principle component analysis (19) was performed to determine linear combinations of the data such that the maximum variance defined as the square of the standard deviation! between the members of the data set was obtained in n mutually orthogonal dimensions.
- the linear combinations of the data resulted in the largest variance or separation! between the members of the data set in the first principle component (pc1) and produced decreasing magnitudes of variance from the second to the n th principle component (pc2-pcn).
- the coefficients required to transform the autoscaled data into principle component space (by linear combination) were determined by multiplying the data matrix, D, by its transpose, D T (i.e. diagnolizing the matrix)(19)
- This operation produced the correlation matrix, R whose diagonal elements were unity and whose off-diagonal elements were the correlation coefficients of the data.
- the total variance in the data was thus given by the sum of the diagonal elements in R.
- the n eigenvalues, and the corresponding n eigenvectors, were then determined for R.
- Each eigenvector contained a set of n coefficients which were used to transform the data by linear combination into one of its n principle components.
- the corresponding eigenvalue yielded the fraction of the total variance that was contained in that principle component.
- This operation produced a principle component matrix, P, which had the same dimensions as the original data matrix. Under these conditions, each row of the matrix P was still associated with a particular odor and each column was associated with a particular principle component.
- FIG. 2 shows the cyclic voltammetric behavior of a chemically polymerized poly(pyrrole) film following ten cycles from -1.00 V to +0.70 V vs. SCE.
- the cathodic wave at -0.40 V corresponded to the reduction of poly(pyrrole) to its neutral, nonconducting state
- the anodic wave at -0.20 V corresponded to the reoxidation of poly(pyrrole) to its conducting state (24).
- FIG. 3A shows the optical spectrum of a processed polypyrrole film that had been spin-coated on glass and then rinsed with methanol.
- the single absorption maximum was characteristic of a highly oxidized poly(pyrrole) (26), and the absorption band at 4.0 eV was characteristic of an interband transition between the conduction and valence bands.
- the lack of other bands in this energy range was evidence for the presence of bipolaron states (see FIG. 3A), as have been observed in highly oxidized poly(pyrrole) (26).
- Sensor arrays consisted of as many as 14 different elements, with each element synthesized to produce a distinct chemical composition, and thus a distinct sensor response, for its polymer film.
- the resistance, R, of each film-coated individual sensor was automatically recorded before, during, and after exposure to various odorants.
- a typical trial consisted of a 60 sec rest period in which the sensors were exposed to flowing air (3.0 liter-min -1 ), a 60 sec exposure to a mixture of air (3.0 liter-min -1 ) and air that had been saturated with solvent (0.5-3.5 liter-min -1 ), and then a 240 sec exposure to air (3.0 liter-min -1 ).
- FIG. 4B-D depicts representative examples of sensor amplitude responses of a sensor array (see, Table 3).
- data were recorded for 3 separate exposures to vapors of acetone, benzene, and ethanol flowing in air.
- the response patterns generated by the sensor array described in Table 3 are displayed for: (B) acetone; (C) benzene; and (D) ethanol.
- the sensor response was defined as the maximum percent increase and decrease of the resistance divided by the initial resistance (gray bar and black bar respectively) of each sensor upon exposure to solvent vapor. In many cases sensors exhibited reproducible increases and decreases in resistance.
- An exposure consisted of: i) a 60 sec rest period in which the sensors were exposed to flowing air (3.0 liter-min -1 ); ii) a 60 sec exposure to a mixture of air (3.0 liter-min -1 ) and air that had been saturated with solvent (0.5 liter-min -1 ); and iii) a 240 sec exposure to air (3.0 liter-min -1 ). It is readily apparent that these odorants each produced a distinctive response on the sensor array.
- Principle component analysis (19) was used to simplify presentation of the data and to quantify the distinguishing abilities of individual sensors and of the array as a whole.
- linear combinations of the ⁇ R max /R i data for the elements in the array were constructed such that the maximum variance defined as the square of the standard deviation! was contained in the fewest mutually orthogonal dimensions.
- the resulting clustering, or lack thereof, of like exposure data in the new dimensional space was used as a measure of the distinguishing ability, and of the reproducibility, of the sensor array.
- FIGS. 6A and 6B show the principle component analysis for all 14 sensors described in Table 3 and FIGS. 4 and 5.
- FIGS. 6A and 6B show the principle component analysis for all 14 sensors described in Table 3 and FIGS. 4 and 5.
- FIGS. 6A or 6B show the principle component analysis for all 14 sensors described in Table 3 and FIGS. 4 and 5.
- FIGS. 6A and 6B show the principle component analysis for all 14 sensors described in Table 3 and FIGS. 4 and 5.
- the same sensor array was also able to resolve the components in various test methanol-ethanol mixtures (29). As shown in FIG. 7B, a linear relationship was observed between the first principle component and the mole fraction of methanol in the liquid phase, ⁇ m , in a CH 3 OH--C 2 H 5 OH mixture, demonstrating that superposition held for this mixture/sensor array combination. Furthermore, although the components in the mixture could be predicted fairly accurately from just the first principle component, an increase in the accuracy could be achieved using a multi-linear least square fit through the first three principle components. This relationship held for CH 3 OH/(CH 3 OH+C 2 H 5 OH) ratios of 0 to 1.0 in air-saturated solutions of this vapor mixture. The conducting polymer-based sensor arrays could therefore not only distinguish between pure test vapors, but also allowed analysis of concentrations of odorants as well as analysis of binary mixtures of vapors.
- This type of polymer-based array is chemically flexible, is simple to fabricate, modify, and analyze, and utilizes a low power dc resistance readout signal transduction path to convert chemical data into electrical signals. It provides a new approach to broadly-responsive odor sensors for fundamental and applied investigations of chemical mimics for the mammalian sense of smell. Such systems are useful for evaluating the generality of neural network algorithms developed to understand how the mammalian olfactory system identifies the directionality, concentration, and identity of various odors.
- a sensor exposure consisted of (1) a sixty second exposure to flowing air (6 liter min-1), (2) a sixty second exposure to a mixture of air (6 liter min-1) and air that had been saturated with the analyte (0.5 liter min-1), (3) a five minute recovery period during which the sensor array was exposed to flowing air (6 liter min-1).
- the resistance of the elements were monitored during exposure, and depending on the thickness and chemical make-up of the film, resistance changes as large as 250% could be observed in response to an analyte.
- a 10 element sensor array consisting carbon-black composites formed with a series of non-conductive polymers (see Table 4) was exposed to acetone,benzene, chloroform, ethanol, hexane, methanol, and toluene over a two day period. A total of 58 exposures to these analytes were performed in this time period. In all cases, resistance changes in response to the analytes were positive, and with the exception of acetone, reversible (see FIG. 8). The maximum positive deviations were then subjected to principal component analysis in a manner analogous to that described for the poly(pyrrole) based sensor.
- FIG. 9 shows the results of the principal component analysis for the entire 10-element array. With the exception of overlap between toluene with benzene, the analytes were distinguished from one and other.
- Cited References 1. Lundstrom et al. (1991) Nature 352:47-50; 2. Shurmer and Gardner (1992) Sens. Act. B 8:1-11; 3. Reed (1992) Neuron 8:205-209; 4. Lancet and Ben-Airie (1993) Curr. Biol. 3:668-674; 5. Kauer (1991) TINS 14:79-85; 6. DeVries and Baylor (1993) Cell 10(S):139-149; 7. Gardner et al. (1991) Sens. Act. B 4:117-121; 8. Gardner et al. (1991) Sens. Act. B 6:71-75; 9. Corcoran et al. (1993) Sens. Act. B 15:32-37; 10.
Abstract
Description
TABLE 1 ______________________________________ Major Class Examples ______________________________________ Organic Conductors conducting polymers (poly(anilines), poly(thiophenes), poly(pyrroles), poly(acetylenes), etc.)), carbonaceous materials (carbon blacks, graphite, coke, C.sub.60, etc.), charge transfer complexes (tetramethyl- paraphenylenediamine-chloranile, alkali metal tetracyanoquinodimethane complexes, tetrathiofulvalene halide complexes, etc.), etc. Inorganic Conductors metals and metal alloys (Ag, Au, Cu, Pt, AuCu alloy, etc.), highly doped semi- conductors (Si, GaAs, InP, MoS.sub.2, TiO.sub.2, etc.), conductive metal oxides (In.sub.2 O.sub.3, SnO.sub.2, Na.sub.x Pt.sub.3 O.sub.4, etc.), superconductors (YBa.sub.2 Cu.sub.3 O.sub.7, Tl.sub.2 Ba.sub.2 Ca.sub.2 Cu.sub.3 O.sub.10, etc.), etc. Mixed inorganic/organic Tetracyanoplatinate complexes, Iridium halocarbonyl complexes, stacked Conductors macrocyclic complexes, etc. ______________________________________
TABLE 2 ______________________________________ Major Class Examples ______________________________________ Main-chain carbon poly(dienes), poly(alkenes), poly(acrylics), polymers poly(methacrylics), poly(vinyl ethers), poly(vinyl thioethers), poly(vinyl alcohols), poly(vinyl ketones), poly(vinyl halides), poly(vinyl nitriles), poly(vinyl esters), poly(styrenes), poly(arylenes), etc. Main-chain acyclic poly(oxides), poly(carbonates), heteroatom polymers poly(esters), poly(anhydrides), poly(urethanes), poly(sulfonates), poly(siloxanes), poly(sulfides), poly(thioesters), poly(sulfones), poly(sulfonamides), poly(amides), poly(ureas), poly(phosphazenes), poly(silanes), poly(silazanes), etc. Main-chain poly(furan tetracarboxylic acid heterocyclic polymers diimides), poly(benzoxazoles), poly(oxadiazoles), poly(benzothiazinopheno- thiazines), poly(benzothiazoles), poly(pyrazinoquinoxalines), poly(pyro- mellitimides), poly(quinoxalines), poly(benzimidazoles), poly(oxindoles), poly(oxoisoindolines), poly(dioxoiso- indolines), poly(triazines), poly(pyridazines), poly(piperazines), poly(pyridines), poly(piperidines), poly(triazoles), poly(pyrazoles), poly(pyrrolidines), poly(carboranes), poly(oxabicyclononanes), poly(dibenzofurans), poly(phthalides), poly(acetals), poly(anhydrides), carbohydrates, etc. ______________________________________
d'.sub.ij =(d.sub.ij -d.sub.i)/σ.sub.i (1)
R=D.sup.T ·D (2)
C=(P.sup.T ·P).sup.-1 ·P.sup.T ·V(3)
PY→PY.sup.·+ +e.sup.- (4)
2PY.sup.·+ →PY.sub.2 +2H.sup.+ (5)
H.sub.3 PMo.sub.12 O.sub.40 +2e.sup.- +2H.sup.+ →H.sub.5 PMo.sub.12 O.sub.40 (6)
TABLE 3 ______________________________________ Plasticizers used in array elements* sensor plasticizer ______________________________________ 1none 2 none** 3 poly(styrene) 4 poly(styrene) 5 poly(styrene) 5 poly(styrene) 6 poly(a-methyl styrene) 7 poly(styrene-acrylonitrile) 8 poly(styrene-maleic anhydride) 9 poly(styrene-allyl alcohol) 10 poly(vinyl pyrrolidone) 11 poly(vinyl phenol) 12 poly(vinyl butral) 13 poly(vinyl acetate) 14 poly(carbonate) ______________________________________ *Sensors contained 2:3 (w:w) ratio of pyrrole to plasticizer. **Film not rinsed to remove excess phosphomolybdic acid.
TABLE 4 ______________________________________ Sensor # Non-Conductive Polymer ______________________________________ 1 poly(4-vinyl phenol) 2 poly(styrene - allyl alcohol) 3 poly(α-methyl styrene) 4 poly(vinyl chloride - vinyl acetate) 5 poly(vinyl acetate) 6 poly(N-vinyl pyrrolidone) 7 poly(bisphenol A carbonate) 8 poly(styrene) 9 poly(styrene-maleic anhydride) 10 poly(sulfone) ______________________________________
Claims (10)
Priority Applications (11)
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US08/689,227 US5698089A (en) | 1995-03-27 | 1996-08-07 | Sensor arrays for detecting analytes in fluids |
US08/986,500 US6010616A (en) | 1995-03-27 | 1997-12-08 | Sensor arrays for detecting analytes in fluids |
US09/006,279 US5959191A (en) | 1995-03-27 | 1998-01-13 | Sensor arrays for detecting analytes in fluids |
US09/006,142 US5951846A (en) | 1995-03-27 | 1998-01-14 | Sensor arrays for detecting analytes in fluids |
US09/095,376 US6013229A (en) | 1995-03-27 | 1998-06-10 | Sensor arrays for detecting analytes in fluids |
US09/154,604 US5891398A (en) | 1995-03-27 | 1998-09-16 | Sensor arrays for detecting analytes in fluids |
US09/183,724 US6170318B1 (en) | 1995-03-27 | 1998-10-30 | Methods of use for sensor based fluid detection devices |
US09/209,914 US6017440A (en) | 1995-03-27 | 1998-12-11 | Sensor arrays for detecting microorganisms |
US10/266,550 US20030159927A1 (en) | 1995-03-27 | 2002-10-07 | Colloidal particles used in sensing arrays |
US10/409,449 US20040033165A1 (en) | 1995-03-27 | 2003-04-07 | Sensor arrays for detecting analytes in fluids |
US11/157,316 US20060034731A1 (en) | 1995-03-27 | 2005-06-20 | Sensor arrays for detecting analytes in fluids |
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US08/410,809 US5571401A (en) | 1995-03-27 | 1995-03-27 | Sensor arrays for detecting analytes in fluids |
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US08/410,809 Continuation US5571401A (en) | 1995-03-27 | 1995-03-27 | Sensor arrays for detecting analytes in fluids |
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US08/689,227 Expired - Lifetime US5698089A (en) | 1995-03-27 | 1996-08-07 | Sensor arrays for detecting analytes in fluids |
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US09/209,914 Expired - Lifetime US6017440A (en) | 1995-03-27 | 1998-12-11 | Sensor arrays for detecting microorganisms |
US10/266,550 Abandoned US20030159927A1 (en) | 1995-03-27 | 2002-10-07 | Colloidal particles used in sensing arrays |
US10/409,449 Abandoned US20040033165A1 (en) | 1995-03-27 | 2003-04-07 | Sensor arrays for detecting analytes in fluids |
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US09/006,279 Expired - Lifetime US5959191A (en) | 1995-03-27 | 1998-01-13 | Sensor arrays for detecting analytes in fluids |
US09/209,914 Expired - Lifetime US6017440A (en) | 1995-03-27 | 1998-12-11 | Sensor arrays for detecting microorganisms |
US10/266,550 Abandoned US20030159927A1 (en) | 1995-03-27 | 2002-10-07 | Colloidal particles used in sensing arrays |
US10/409,449 Abandoned US20040033165A1 (en) | 1995-03-27 | 2003-04-07 | Sensor arrays for detecting analytes in fluids |
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KR100389603B1 (en) | 2003-10-08 |
PT820585E (en) | 2000-06-30 |
GR3033092T3 (en) | 2000-08-31 |
DE69605906D1 (en) | 2000-02-03 |
MX9707351A (en) | 1998-03-31 |
FI973802A0 (en) | 1997-09-26 |
ES2144737T3 (en) | 2000-06-16 |
US5571401A (en) | 1996-11-05 |
JP3963474B2 (en) | 2007-08-22 |
JPH11503231A (en) | 1999-03-23 |
EP0950895A3 (en) | 2002-01-02 |
EP0950895A2 (en) | 1999-10-20 |
ATE188291T1 (en) | 2000-01-15 |
CN1184530A (en) | 1998-06-10 |
DK0820585T3 (en) | 2000-06-19 |
KR19990014748A (en) | 1999-02-25 |
FI973802A (en) | 1997-09-29 |
US6017440A (en) | 2000-01-25 |
US6010616A (en) | 2000-01-04 |
AU705825B2 (en) | 1999-06-03 |
EP0820585B1 (en) | 1999-12-29 |
CA2215332C (en) | 2006-11-21 |
US20040033165A1 (en) | 2004-02-19 |
CA2215332A1 (en) | 1996-10-03 |
EP0820585A1 (en) | 1998-01-28 |
DE69605906T2 (en) | 2000-07-13 |
US5959191A (en) | 1999-09-28 |
CN1179208C (en) | 2004-12-08 |
RU2145081C1 (en) | 2000-01-27 |
US20030159927A1 (en) | 2003-08-28 |
WO1996030750A1 (en) | 1996-10-03 |
JP2006010703A (en) | 2006-01-12 |
AU5372896A (en) | 1996-10-16 |
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